Linear predictive coding

About: Linear predictive coding is a research topic. Over the lifetime, 6565 publications have been published within this topic receiving 142991 citations. The topic is also known as: Linear predictive coding, LPC.

Speech coding apparatus

Abstract: A speech coding apparatus which selects an optimum code from a code book (21), the optimum code giving the minimum magnitude of error signal between the input signal and the reproduced signal obtained by a filter calculation using a linear prediction parameter from a linear predictive analysis unit (10) with respect to the codes of the code data, wherein use is made, as the codes, of a code formed by thinning to 1/M (M being an integer of two or more) the plurality of sampling values constituting the codes. To compensate for the deterioration of the quality of the reproduced signal caused by thinning the sampling values in this way, an additional linear predictive analysis unit (20) is further introduced and use made of an amended linear prediction parameter instead of the linear prediction parameter.

A 16, 24, 32 kbit/s wideband speech codec based on ATCELP

Abstract: This paper describes a combined adaptive transform codec (ATC) and code-excited linear prediction (CELP) algorithm, called ATCELP, for the compression of wideband (7 kHz) signals. The CELP algorithm applies mainly to speech, whereas the ATC mode is selected for music and noise signals. We propose a switching scheme between CELP and ATC mode and describe a frame erasure concealment technique. Subjective listening tests have shown that the ATCELP codec at bit rates of 16, 24 and 32 kbit/s achieved performances close to those of the CCITT G.722 at 48, 56 and 64 kbit/s, respectively, at most operating conditions.

Vector quantization techniques for output-based objective speech quality

Abstract: Output-based speech quality (OBQ) refers to objective speech quality assessment using only received speech without utilizing the input speech record. This paper proposes three new OBQ measures and evaluates their performance. Parameters derived from perceptual linear prediction (PLP) coefficients are used to provide speaker independence required by the objective measures. PLP, PLP cepstrum, and PLP delta-cepstrum parameters are computed for output speech records from an undistorted source speech database and vector quantized. The resulting codebook provides a reference for computing objective distance measures for distorted speech. The proposed objective measures are the transition probability distance, the median minimum distance, and the chi-squared distance. The OBQ parameters are tested on four different speech datasets, and correlation is computed between subjective scores and objective distances under a variety of conditions. The results indicate that the proposed algorithms are robust against speaker, text, and distortion variation.

Blind speech separation of moving speakers in real reverberant environments

Abstract: In this paper we present a new on-line blind signal separation method capable to separate convolutive speech signals of moving speakers in highly reverberant rooms. The separation network used is a recurrent network which performs separation of convolutive speech mixtures in the time domain, without any prior knowledge of the propagation media, based on the maximum likelihood estimation (MLE) principle. The proposed method proved to be able to improve significantly (more than 10% in all adverse mixing situations) the performance of a continuous phoneme-based speech recognition system and therefore can be used as a front-end to separate simultaneous speech of speakers who are moving in arbitrary directions in reverberant rooms.